Body part imaging method

ABSTRACT

An imaging method places an object upon a background pattern of regular repetitive marks and records a 2D image that is then processed for determining where in the image the repetitive marks are interrupted by the object, thereby indirectly determining the edge of the object. Multiple 2D images from different perspectives are used to create a 3D image of the object. When the object is a human food, individual bar codes and imaged foot dimensions can be cross-referenced to manufactured shoe sizes for accurate ordering of correctly sized footwear.

REFERENCE TO RELATED APPLICATION

The present application is related to applicant co-pending applicationentitled “Body Part Imaging System”, filed May 1, 2000, Ser. No.09/562,842, by the same inventor.

FIELD OF THE INVENTION

The present invention relates to imaging of human body parts. Moreparticularly, the present invention relates to imaging the edges of abody part or an object, such as a human foot including the footprint,arch and instep using a patterned background.

Conventional measurements of 3-D objects have used a laser scanners orarea image sensors that scans the area of the object to be imaged. Thesensors may be CMOS or charged coupled device (CCD) sensors, such asused in a digital camera. The scanners may be a single line CCD scanneror a PC scanner. Generally, the overall dimensional of an object aremeasured by imaging the edges of the object. The periphery of the objectis constructed when imaging object edges that are contrasted from adifferent colored background. The edge of the object is interpretedusing software algorithms that discerns transitions from the edge of theobject from the space behind the object. The space behind the object hasto have some degree of color from white or black different from theobject so that the data input to an image processing algorithm canindicate the edge of the object. The edges of an object are oftenblurred or indiscernible from the background as a result of shadowing orthe use of similar colors between the background the object. When theobject being measured has any edges of a color similar to thebackground, the algorithm fails to accurately detect the edges, andhence the algorithm inaccurately determines the edges of the object.When the object is multicolored, it is often difficult to accuratelydiscern the edges of the object as the background will merge wit theedges of the object. The inability to accurately detect edges leads toinaccurate sizing of three-dimensional (3D) objects. When contourimaging a 3D object using imaged edges, the scanning or sensing meanscircumscribes the 3D outline of the object by moving the sensor aroundthe object to image plurality of edges around the object. The 3D imageof the object then constructed will be made up of the continuous outsidedimensions of the object and will accurately display the outermostdimensional contour of the object.

Other methods of imaging 3D objects include laser imaging methods thatmeasured the depth of laser projected light beams as the beams arereflected back to a detector using beam deformation and position changesto image depth. Typically, the detector used with the laser detects theposition of the laser beam over the entire surface of the object as thelaser is moved. The laser imaging method often fails due to color,texture and reflection of the imaging laser beam. In both scanning andlaser methods, the software algorithms are complex because the imagingprocess requires scanning and detecting areas of objects having lightintensity such that the detector means may not be able to definitivediscern the edge of the object. To detect the edges, predictionalgorithms are used to fill in areas of the object that are impreciselydetected. Typically, the software algorithm is complex and slow andinherently unreliable. These and other disadvantages are solved orreduced using the present invention.

SUMMARY OF THE INVENTION

An object of the invention is to provide a system and method thatindirectly images objects by contrasting the object with a predeterminedbackground pattern.

An object of the invention is to provide a system and method thatindirectly images objects by contrasting the object with a predeterminedbackground checkerboard grid pattern of alternating white and blackcolored areas.

Another object of the invention is provide a system and method forcross-referencing human body and body parts dimensions to manufactureapparel sizes for accurately ordering apparel form manufacturers.

Another object of the invention is to provide a means of capturing boththe weighted and non-weighted variations of feet to enable the imagingof arch height and type, and the spread of the feed under weight.

The invention is directed to an imaging system and method thatindirectly measures an object using a background pattern. An object tobe measured is placed in front of a predetermined background grid.Imaging means image the background pattern that is interrupted by theobject placed in front of the background pattern. The system and methodimages the background pattern. When the ordered regularity of thebackground pattern is interrupted by the object, the edge is accuratelydetermined by counting the number of alternating areas, such as blackand white areas, from a known border of the background pattern or fromother predetermined fixed reference locations, targets or purposefulirregularities within the background pattern. Software algorithms thendetermine the overall measurement of the object where the backgroundpattern has been interrupted to indirectly measure the periphery of theobject. A plurality of images taken from different perspectives provideaccurate 2D peripheral measurements that are combined to provide a 3Dmeasurement of the object being measured.

The imaging means may include an array of light detecting cells such ascharged coupled devices (CCD) or complementary metal oxide silicon(CMOS) area sensors. These sensors are commonly used in a digitalcameras having appropriate lenses that focus the image to impinge theimage over an image area onto the area sensors. The image in digitalform can be stored in a processing system such as a personal computer. Acomputer processing system is used to process the stored image during animaging process. A plurality of images may be stored for respectivedifferent angle positions of the imaging means. Preferably, for eachimage recorded, the imaging process counts repetitive marks toreconstruct the visible area of the background pattern. The repetitivemarks are preferably blocks in rows and columns of alternating black andwhite blocks of a preferred checkerboard background pattern. Therepetitive marks are counted starting from a known edge position usuallyknown as a reference target.

The imaging process processes the stored image by determined the edge ofthe object relative to interruption in the regularity of the backgroundpattern. An expected error of one or two blocks, that is, the backgroundpattern image tolerance error, can occur depending on the color of theobject being imaged contrasted from the color of the background pattern.Each background pattern, area, mark or block, may be as small as isdetectable by the sensor means. In the case of a checkerboard patternimaging a human foot, for example, the block dimension may be only onemillimeter and well within sensor and focusing lens capabilities.Conventional edge average smoothing processes maybe be performed duringcomputer image processing to obtain an average edge contour linedepicting the edge of the object accurate to plus or minus one blockdimension. Each mark or block represents a fixed dimension. Counting thenumber of marks or blocks from a plurality of reference targets or fromfixed patterned borders will enable by imaging processing, a method fordetermining the dimensions of the object being measured within one markor block dimension.

The background pattern only needs predetermining contrasting marks forimage recognition and processing. Alternating checkerboard blocks is thesimplest to make and use as the preferred background pattern. However,there are several other types of background patterns that may be used.For example, Fresnel patterns may be used where each block deflects thelight to appear like lighted and unlighted blocks to the sensor means.For another example, a sublighted platform where black blocks areprinted on a clear or translucent bottom material so that light emanatesupward through the light translucent blocks. The sublighted platform isadvantageous because it eliminates top lighting shadows. Other patternssuch as circles, rectangles, triangle, hexagons, among many other, couldbe used as well, for different applications and accuracy considerations.

The accuracy of the imaging process system and method is determined bythe area, mark or block size of the background pattern. Each repetitivebackground pattern mark or block in the chosen background pattern willhave a predetermined minimum number of imaged pixels that is greaterthan one. The sensory means provides an adequate number of pixels toimage the marks or blocks in the background pattern. Each mark or blockshould have at least two pixels per mark or block in the backgroundpattern. The sensor means must accurately detect each individual markover a field of view (FOV), such as over a predetermined area of thewhite or black blocks in the checkerboard pattern when no object isplaced in front of the background pattern. The FOV determines the lensfocusing requirements for the sensor means. The lens focusing of thesensor means and the number of pixels over the FOV area to be measuredmust be such as to have at least two pixels focused on each coloredblock. When using more than two pixel per mark or block, the resolutionand resulting quality of the process image is enhanced with improvedresolution.

When an object of any color or pattern is placed within the checkerboardarea, the imaging means detects an interference in the order ofrepetitive marks of the background pattern. In the case of acheckerboard background pattern, the regularity of the white to blackblock images are interrupted by the object. Of course, the object shouldnot have a colored pattern the same as the background pattern. Adetection tolerance error can occur when the object being imaged has acolor pattern that matches the pattern of the background and when theobject pattern is perfectly aligned with the background pattern, when isa highly unlikely event. Various background patterns may be used toaccommodate the imaging of any arbitrary colored object.

A preferred use of the invention is for sizing a human being, moreparticularly, human feet for selecting suitably sized footwear and humanbodies for selecting suitably sized clothing. In the case of footwear,great care is needed to provide accurate foot measurements and sizedshoes, less the person wearing incorrectly sized fitted shoes may besubject to discomfort and even damage and injury to the feet.

The important parts of a foot to be measured are the periphery of thefoot, including the length and width of the foot, as seen from the topof the foot over the approximate center of the forefoot, the side viewof the instep and the side view of the arch. In the operation of thesystem and method, the foot is placed on a floor mat that is printedwith an alternating checkerboard pattern preferably in black and whiteone millimeter blocks. As the scanned pixels in the CCD reach the edgeof the foot being scanned, the color could be anything and the output ofthe CCD could be any voltage between zero and full scale, such as fivevolts. However, the CCD output sensor will still put out a zero or a onedepending if the CCD output is greater than or lesser than one half ofthe full scale, such as 2.5 volts. From an edge border or target of thecheckerboard reference to when the edge of the object is indirectlyobserved, there will be a discontinuity in the regular pattern of blocksimaged in the presence of the edge of the objects. The discontinuity isdetected by a change in the regular image pattern. The computer processmethod will scan for discontinuities over the FOV area covering theplacement of the foot all the way from the reference target positions ofthe checkerboard to the edge of the object being imaged. An image mapwill be compiled and stored in memory indicating each location point ofdiscontinuity. The location points will trace an edge of the image ofthe foot. Repeated images taken from the sensor means at variousrelative angle to the foot, are then used to create a 3D image of thefoot. Computer processing can convert the 2D images into a single 3Dimage of the foot.

In this manner, the system and method enables the creation of a 3D imageof an object, such as a foot, by sensing the extent of a backgroundpattern within a field of view to create a 2D image at a respectiverelative angle between the sensor and the object placed on a backgroundpattern. The processing method indirectly determines the edge of theobject on the background pattern at pixel locations relative to one ormore reference targets to where the regular background pattern isinterrupted by the object. The processing method converts the 2D imageof the interrupted background pattern into a 2D edge image of theobject. Multiple 2D edge images taken from different perspectives arecombined together to create a 3D image of the object. During imaging ofa foot, a unique bar code associated with the object being image isplaced within the FOV and is imaged by the same sensor so as toassociate a bar code with the image foot.

Once a body part, such as a foot, has been imaged by scanning and thendimensioned by computer processes imaged into precise foot dimensionsincluding the top of the foot periphery, arch and instep, the footdimensions are crossed referenced to the bar code for identifying theindividual of the foot that was imaged. The foot dimensions can then becross-referenced to the inside dimensions of footwear types sold byvarious footwear manufacturers. An individual then need only provide aretailer with an identification of the bar code card. Retail processingmethods can then cross reference the bar code card and corresponding barcode to the imaged foot dimensions that are in turn cross referenced tothe correct footwear size so that a customer can be provided with thebest fitting footwear size produced by the footwear manufacturer,thereby, improving the footwear procurement process eliminating to alarge extent returns of footwear due to incorrect sizing. These andother advantages will become more apparent from the following detaileddescription of the preferred embodiment.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a side view of a human foot inserted into a measurementsystem.

FIG. 2 depicts a top view of two human feet inserted into a measurementsystem.

FIG. 3 depicts a front view of the measurement system.

FIG. 4A depicts a foot top and arch scanning procedure geometry.

FIG. 4B depicts foot arch scanning geometry.

FIG. 4C depicts foot top scanning geometry.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

An embodiment of the invention is described with reference to thefigures using reference designations as shown in the figures. Referringto FIG. 1, a human foot as shown is disposed on a patterned floor planeand in front on a patterned back plane. The patterned floor plane andback plane have, in the preferred form, a checkerboard print, only partof which is shown for convenience, but the print preferably extends overa field of view (FOV) of a camera. The checkerboard print is partiallyshown for convenience to be alternative square block of white and crosshair blocks, the later of which is actually printed as solid blocks. Thefield of view angularly extends from the focusing camera so as tocapture in the FOV the human foot features desired to be imaged. Thepatterned print of the background plane and the floor plane extendsthroughput the FOV. Targets are used to provide relative referencepoints to the checkerboard prints so as to reference displacement of thehuman foot relative to the blocks of the checkerboard print. The camerafocuses upon the checkerboard pattern to image the foot and thecheckerboard print area to capture the FOV image. The camera provides adigital image to a computer processing means that processes the digitalimage. The image is captured by the camera as a two-dimensional (2D)image containing the reference target points, and the checkerboard ofalternating blocks having patterned regularity that is interrupted bythe presence of the human foot. The computer is further used to controlthe position of the camera through a camera position range by actuatinga motor so as to capture a plurality of desired 2D images at differingfocusing angular views. The computer processes the plurality of captured2D images into a 3D image of the outermost periphery of the footresulting in outermost 3D dimensions of the human foot. A bar codeidentification card is disposed within a bar code cardholder alsoposition within the camera FOV. The bar code of the bard code card is acode that uniquely identifies the human foot to a particular human beingso that the computer processes can cross reference the particular humanbeing to the respective 3D image and the resulting 3D dimensions of thefoot. The computer can further store data cross referencing shoe sizesof a particular shoe manufacturer to the 3D dimensions of the 3D imageso that the computer can determine the appropriate shoe size of theparticular manufacturer for the particular feet of the particular humanbeing. By cross-referencing the identification card to the bar code tothe peripheral size and shape of the measured foot to the inside cavitydimensions and shape of the footwear.

Referring to FIGS. 1, 2, and 3, and more particularly to FIGS. 2 and 3,an alternative dual imaging embodiment may be used to concurrentlycapture 2D images of a pair of human feet, a left foot and a right foot.The two feet are disposed on a double patterned floor plane with thecamera capturing a pair of respective 2D images for the respective feet.As shown, there is a single camera traversing the vertical range, havingtwo FOVs extending horizontal. The camera captures left and right imagesthrough two respective left and right FOVs. The camera can be a singlecamera that views from one perspective FOV then is pivoted 180 degreesor two cameras vertically translated by the motor in tandem to view bothperspective FOV at the same time. The camera and the patterned floor andback planes function in combination as a scanning mechanisms that ineffect scans through scanner sweep ranges that are FOVs of the camera.The patterned floor plane is divided into respective left and righthalves, each having a respective pair of referencing targets. Verticallyextending and opposing left and right backplanes are used to image thevertical height features of the respective human feet. The verticallyextending back planes also contain targets, not shown. All of thetargets are used to provide reference points for referencing thepositions of the blocks within the planes to a known location in advanceof imaging. The bi-directional imaging camera is shown to traverse thevertical camera position range. Left and right top cameras are shown tohave FOVs extending downward towards the respective pattern floor planehalves to image the outside periphery of the respective feet, and moreparticularly the forefoot of the feet extending towards and to almostthe heel. The heels of the respective feet are shown to be disposed inrespective heels cups for proper positioning of the feet on therespective patterned floor planes halves.

The camera may be an exemplar charged-complex-device (CCD) sensorimaging means used to capture a 2D image and output the captured imagein digital form. The image is captured preferably through the sequentialscanning of CCD detectors. Conventional CCD cameras may be used forimaging in the preferred form. The image comprising the subject foot andbackground checkerboards is focused by a lens of the camera onto asilicon chip CCD X-Y array of light detectors representing respectiveX-Y pixels. A CCD controller of the camera raster-scans the X-Ydetectors. When each pixel detector is scanned, an analog value of thelight intensity is provided and represents the light intensity for arespective pixel at a particular X-Y coordinate in the X-Y area. The CCDimaging means is fed a clock pulse that advances through each pixeldetector by row and by column in a raster scan so that an output of theCCD sensor is provided for each pixel by row and by column, serially,one at a time, until sequencing through all the pixels of the capturedimage.

The camera captures the black and white blocks of the checkerboard aswell as the imaged foot. Each block is captured as two or more pixelshaving the same substantial output analog value. During image areacapturing, the camera generates an analog value of the returned lightfor each pixel. In the preferred form, monochrome gray-scale imageprocessing is used. For simplicity in constructing a body contour, thewhite of black imaging through gray-scale conversion is suitable,through other color schemes could be used as well. An analog output forthe CCD sensor has a dynamic range between zero and full scale, such asfive volts, for spanning the gray-scale values between black togray-scale values to white. The output of the CCD sensor may be coupledto level detector, not shown, that is set to one half of the full scalevalue, such as 2.5 volts, for digitizing the CCD gray-scale analogoutput into a data stream of zero and one bits for computer imageprocessing. Anytime a pixel is sensed from below medium gray to black,the output of the comparator would be below the one half of full scaleand the pixel would be digitized a zero bit, and, anytime a pixel issensed from medium gray to white, the output of the comparator would bedetected above 2.5 volts and the pixel would be digitized as a one bit.When the CCD sensor includes an analog to digital converter (DAC), suchas an 8 bit DAC, then the most significant bit of the DAC output wouldbe the center value of the gray-scale and this most significant bit isthe digitized zero or one bit output to the computer processing means.Even though a CCD with a DAC built on-board provides digital outputsrepresenting the whole dynamic range of the output intensity sensed,only the halfway point is needed to discern an edge of an object. Yet,the computer image processing could process a multiple bit output of thegray scale or color scale for enhanced image processing. In thepreferred form, only edge detection is required and only zero and onedigital bit intensity resolution is required.

Imaging processing operates upon pixel digitization. Each white or blackblock of the checkerboard pattern is processed by sensing at least fourpixels, two pixel in each of the X rows and Y columns. Along each row orcolumn, each block on the checkerboard is determined by at least twopixels having the same value. A corresponding digital pulse train fromthe camera is provided to the image processing computer during theraster scan of the image. The pulse train provides a sequence oftransitions that occur every block transition when transiting betweenblack and white blocks. The pixel pulse train would include transitionlevels of alternating zero and one values along each column and row ofthe captured image, and the computer processing can recognize thepattern of transitions in the pulse train to determine which receivetransition corresponds to which image block. The length between thetransitions indicates the number of like zero or one digitized plane. Alimited amount of variations in pulse widths between transition for eachblock includes an inherent tolerance of +/− one pixel. Each block of thecheckerboard pattern is not imaged at a perfect right angle, and hencethe detected image will naturally have a progression in the number ofpixels per block across the rows and across the columns. Thecheckerboard pattern and the resulting captured image will provide aprogressive number of pixels per blocks greater than two pixels perblock to cause the progression of pixels per block to vary in aprogressive manner. The progression of the number of pixels per blockmay cover a large range across the entire row or column of the capturedimage. For example, in the case of the floor checkerboard pattern, inthe near field, at one extreme, the number of pixels per blocks may bethree, and in the far field, at another extreme, the number of pixelsper blocks may be seven, with the number of pixels per blocksprogressively increasing from the near field to the far field along acolumn or row of pixels. For another example, in the case of the backplane checkerboard pattern, or in the case of the floor checkerboardpanel image by an over had camera, from a center located block, therange number of pixels per block may be at minimum, such as three pixelsper block, progressively increasing towards blocks located at the edgeof the checkerboard. Computer image processing can detect regular blockpixel lengths, and can determine the progression in block pixel lengths.For example, a series of transitions of three pixels per blocks followedby a series of transitions of four pixels per blocks, indicates anatural progressive increase in the number of pixels per block, andwould not thereby indicate an interruption of the pixelized image of thecheckerboard. The computer image processing can recognize when the blockpixel lengths have increase or decreased in a progressive manner acrossrows and columns of the captured image.

When a transition from a first block pixel length is followed by atransition of a second block pixel length, the change should be withinthe +/− one pixel tolerance, allowing for the average progressive changein the block pixel length through a row and column. The error indigitization is at least +/− one pixel accounting for the edge of block.The +/− one pixel error can be compensated for by smoothing to providean enhanced contour image. The +/− one pixel errors tend to render theobject smaller then the actual size because the interruption will occurafter the edge is encountered when scanning the checkerboard blockstowards the foot edge. The block error that can be tolerated andcompensated through smoothing is typically twice the block size. Theaverage block error can be partially compensated by subtracting oneblock from the block count to the encountered edge. When a change inblock pixel length, that is the pixel duration between transitions,exceeds the +/− one pixel tolerance, the computer image processing canrecognize this abrupt change as an interruption in the progressive blockpixel length. The computer processes can detect this abrupt change inthe transition period indicating an interruption in the progression ofthe block pixel length so as to then indicate and determine when thecheckerboard pattern has been interrupted by the presence of the bodypart being imaged. Hence, each block is digitized into a number ofpixels per block for each square block, and this number progressivelyincreases or decreases across rows and columns in the FOV. Each block ispositioned at a predetermined distance from the checkerboard patterntarget. The checkerboard target preferably has a unique pixeldefinition, such as a very large square block, recognized as such by theimage processing computer. The target can be replaced by simple edgecheckerboard detection, by referencing the start of the checkerboardpattern at the edge of the checkerboard. The checkerboard edge thenproviding a reference point, as does the target, to the remaining blocksfor block position count determination. Block position countdetermination is achieved by counting the number of the blocks from thereference point, be it a special target or a checkerboard edge, or othersuitable image reference. Hence, the image processing computer receivesthe pixel pulse train and determines, while counting the blocks in boththe rows and columns, at what X-Y block position in the checkerboard theblock pixel length has been abruptly interrupted, thereby providing theX-Y block interruption position indicating a detected edge of the imagedfoot. When the order of alternative blocks, that is, the order ofalternating transitions of a number of pixels per block +/− one pixel isdisrupted, this disruption indicates that the foot edge interrupts theimage of the checkerboard pattern. The disruption in the predeterminedorder of transitions is recognized as an abrupt interruption of theimage of the alternating white and black blocks of alternatingtransition of the number of pixels per block +/− one pixel. Thedisruptions of the foot edge appear as truncated or extended number ofpixels of the alternating transition. For example, a transition betweenone to three pixels in duration, in the two pixels per block range,indicates an abrupt interruption of the transition pulse train, andthereby indicating an abrupt interruption of the image checkerboardpattern by the presence of the edge of the human foot. The imageprocessing computer determines the interruption location along each rowand column and the checkerboard for each 2D image. With multiple 2Dimages, the computer processes can indirectly determines the peripheryof the imaged human foot disposed in front of the checkerboard.

Referring to all of the Figures, and more particularly to FIGS. 4A, 4Band 4C, the vertically traversing imaging camera capture images atvarious vertical positions to generate multiple 2D images. As indicatedin FIGS. 4A, 4B and 4C, the vertical imaging camera captures images atvarious vertical positions, Y1, Y2 and Y3. The captured imaged includethe checkerboard patterned of the floor and black planes. Thecheckerboard pattern is interrupted by the presence of the foot atrespective block positions. In FIG. 4A, for vertical camera positionsY1, Y2, and Y3, the floor plane checkerboard pattern is interrupted atX1, X2, and X3 horizontal floor plane block positions, respectively, andthe back plane checkerboard pattern is interrupted at X4, X5 and X6vertical back plane block positions, respectively.

To measure the outside periphery of a foot as viewed from the top of theforefoot, the top left and right cameras are used in the over head abovethe forefoot about midway between the toe and the front of the leg forthe longest foot expected to ever be measured when the foot is againstthe back heel-cup. The FOV of the over head camera would then cover asfar back to the heel as possible, adequate to measure the forefoot ofthe shortest foot to be measured. The heel cup could be moved slidablyforward for very small feet into the FOV of the over head camera. Theover head camera does not measure the heel periphery because the ankleand leg will shadow the hell cup, but additional cameras could be usedto image the heel if desired. The important part of the foot to image isthe part of the forefoot in front of the ankle.

To image the side of the foot to capture the outline of the insteprequires that the camera be placed on the medial side of the foot andwith a back plane of the checkerboard pattern extending vertically onthe lateral side of the foot. The foot instep is disposed at aparticular gap distance from the vertical checkerboard back plane whilethe camera is vertically positioned at a particular elevation for eachcapture 2D image. Various instep heights will not be accurately measuredby a single 2D image because of angular position errors resulting fromdiffering foot gap distances and at a particular camera elevation.Because the instep height of the feet will significantly vary fordifferent feet, it is necessary to compensate for the angular error.Elevating the camera by motor control to varying elevations enable thecapturing of multiple 2D images to adequately image the instep. When thecamera takes multiple 2D images at respective multiple vertical heights,the number of pattern row and column blocks counted down from the topwill change. Through triangulation computer processing, the actualheight of the instep can be calculated from the plurality of 2D images.The more 2D images taken, the more accurately the instep heightcalculation will be.

The arch height on the medial side of the foot is an important archdimension used to build an arch support. The arch height can be imagedby the camera taking the plurality of 2D images. By positioning thecamera with reference to the floor at various elevations, and takingmultiple images of the arch area, the camera will image the floor planecheckerboard pattern at various respective angles. The floor planecheckerboard pattern is imaged to the extend not blocked by the presenceof the foot. The presence of the foot will interrupt the regularity ofthe imaged background pattern blocks. The arch height and position ofthe foot determines the extend of uninterrupted checkerboard patternimaging. The higher the arch of the foot is, the more checkerboardblocks will be counted under the arch from the target position. Toadequately determine the contour of the arch, the camera is movedincrementally vertically while taking multiple 2D images. As the cameramoves upward, fewer floor plane horizontal blocks will be countedbecause the rising arch will interrupt imaging of the floor plane blocksin varying amounts. The digitized 2D image information is fed to theimage processing computer that in turn calculates the arch height andapproximate configuration shape by performing a series of triangulationcalculations. As the vertical position of the camera is increased, thenumber of horizontal floor blocks counted is decreased because of theinterruption of the captured image by the presence of the foot. At thelowest Y1 camera position, the farthest position under the arch will beseen at the largest number of blocks imaged and counted. In the exemplarform, when the camera is positioned at the Y1 elevation, the value thatrepresents the lowest line of sight is the Y1,X3 line that relates tothe largest number of horizontal blocks from the camera to the X3position at Y1 number of blocks in elevation. The number of horizontalblocks can be determined from the number of horizontal blocks from thereference point that is in turn at a predetermined number of horizontalblocks from the camera. This means that X1 number of horizontal blocksis seen under the foot when the camera is at the Y1 vertical position ofY1 number of blocks high. The horizontal values of X blocks for otherlines of sight at respective camera elevations can be also determinedduring imaging. With three captured images at respective increasingvertical positions, a virtual imaging triangle is create fortriangulation computation purposes providing three intersecting pointsdesignated (ax,ay), (bx,by), and (cx,cy). The segment between (bx,by)and (cx,cy) forms the hypotenuse of a virtual triangle having a centerpoint that is the closest approximation of the actual contour point onthe arch which is determined to be the edge location. By moving thecamera along the vertical dimension, additional virtual lines can becreate and additional virtual triangles can be created, the center ofeach hypotenuse representing the closest approximation contour points ofthe edge of the rising arch as viewed from the vertical position. Morethan three images provide center points that will describe the contourof the arch along a cross section of the foot for constructing the 3-Dimage and dimensions of the arch.

It may now be apparent that the same triangulation calculation methodcan be used to describe the instep of the foot. The difference beingthat in instead of counting the blocks on the floor plane checkerboardpattern, the camera focuses on the vertical back plane checkerboardpattern on the lateral side of the foot where the foot is positionedbetween the camera and the vertical back plane. The processing requiresthat the vertical height position of the camera positional range exceedthe highest instep height. The higher the camera can be moved withreference to the highest part of the instep determines the amount of thelateral side of foot that can be seen by the camera and hence how fardown the lateral side of the foot can be measured. By using this imagingmethod, it is possible to describe the top of the instep at anylongitudinal block position between the toe and the heel as an arc overthe top of the instep where the peak position of the arc is known withrelation to the lateral and medial sides of the foot. The generaloutside shape of the leading and falling sides of the arc arediscernable and calculable within the angle of the FOV of the camera.

While the preferred embodiment is directed towards imaging a foot, thesame method can be applied to imaging an entire human body, or anyarbitrary object. For full body imaging, a larger vertical plane ofcheckerboard pattern is used. The camera views a section of area at atime depending on the number of pixels in the CCD camera and the focusedFOV. The size of the section is determined by the size of thecheckerboard blocks and the number of pixels per block. Because the bodywill be some distance from the vertical checkerboard plane, the camerawill need to assume several locations both horizontal and vertical sothat the same method of triangulation calculation can be used to producethe curved edges of the human body being measured. A group of two setsof images may be taken, for example, a first set of images are of theback of the person with the back of the person facing the camera, and asecond set of images are of the side of a person with the side of theperson facing the camera. This group of images would provide 2D imageinformation to reconstruct the 3D profile of a person. To expediteimaging, at increase costs, a plurality of cameras could be placedvertically and staggered from each other so that all of the cameras movein unison when actuating the motor. The cameras could be driven byanother motor that moves the camera in the same plane as thecheckerboard back plane from one side to the other such as left side toand from to right side. As the cameras move from one side to the other,the body will block the checkerboard pattern at various amountsdepending on the line of sight, and the triangulation calculation wouldproduce the body contour image. More than one camera may be used alongthe vertical direction to cover the full height of a tall person. Theperson may be sectioned into elevation bands wherein a plurality ofimages is taken. The number of bands is determined by the size of thecheckerboard blocks and the number of pixels imaged in each block. Theperson being imaged may further stand on a rotating platform thatrotates the vertical axis of the person so that for each stop positionof the platform, the camera/s perform a sweep to capture the number ofblocks hidden by the shadow of the body of the periphery of the body.The peripheries at a number of rotational positions are thus measuredand recorded to build a series of dimensions for a number of elevationon the body and for a multiplicity of points around the body. Thecomputer can then use best curve fitting algorithms to smooth betweenthe points to produce a full body 3-D image with accurate dimensions.For full body scanning, the person would modestly wear snug fittingclothes to display the actual body contours.

In may further be apparent, that other imaging system configurationscould be used to take advantage of indirect imaging processing using thebackground checkerboard pattern. Furthermore, the block could berectangles or other shapes to meet desired accuracy in each X-Ydimension. The camera should be replaced with a single line CCD sensorsuch as a typical desk scanner and then moved across bands as scannedline images sequentially. The checkerboard pattern could be replacedwith a wall of checkerboard physical bumps that would enable a laser toscan the physical checkerboard pattern as sequential group of regulardepth changes interrupted by the edge of the object when the transitionordered sequence is abruptly interrupted. The laser would be moved orthe laser beam reflected across bands of imaged lines.

Each foot can be imaged, one foot at a time to reduce the number ofcamera used and checkerboard required. Suitable lighting means is usedto reduce shadows to provide equal and adequate imaging of all of theblocks on the checkerboard. The blocks could be colors other then justblack and white, to provide enhanced calculated positions without theuse of a target. The interruptions could be computed from the edge ofthe checkerboard rather than from the target so that the target is notused, but in either case, a relative reference point is needed todetermine the distance from a known point to the point of imageinterruption. Overprinted colors could be used to increase resolution orimprove the edge detection depending on the color and physicalconfiguration of the object to measure. The camera movement ispreferably linear for simplicity, however, moving the elements in an arcthat somewhat follows the contour of the object to be measured could beused for enhanced resolution and increased area coverage. The regularpattern of the checkerboard squares may be progressively dimensioned tocompensate for the progression in angular error with the distance fromthe lens so that all of the resulting transition outputs have the samenumber of pixels per blocks. The checkerboard could also incorporatespecific pattern interruptions that are sensed by the computer astargets for position accuracy check or other detection or verificationreasons. Such purposeful interruptions could be used to calibrate thecamera field and pixel organization or linearity.

Without a foot in place, the camera can observe all of the alternatingblocks across the entire FOV. The camera can be used to check thecleanliness of the checkerboard pattern and then for use for calibrationof the light intensity for readjusting the medium gray-scale point thatdifferentiates white from black blocks. When the checkerboard is soiledby dirt or body oils, the orderly progressive sequence of blocks couldbe interrupted thus indicating that the pad needs to be cleaned duringcalibration testing. For compensation during use prior to cleaning, thelight intensity may be increased to compensate for the reduction inwhite block reflection due to being soiled when it becomes slightly lessthen pure white.

To properly adjust the light source to optimize the sensor detection andto compensate for light source variations due to power fluctuations andbulb life and to some degree to compensate for the cleanliness of theimaging checkerboard pattern, each sensor FOV which also includes alight source to illuminate the FOV includes a series of increasing graydensity blocks in a specified location not ever covered by the objectbeing measured. The light reflected from the different gray densityblocks is proportional to the intensity of the light source. The powerapplied to the light source is controlled by a light dimmer controlledby the computer which in turn receives light intensity values from thecamera for the blocks in question. The dimer controls the power appliedto the light bulb so that the intensity is adjusted to provide a zero orone output for a specified pair of gray density blocks. This lightadjustment is then used for the balance of the measurement session. Thisassures that the light level is accurately controlled at all time.

As may now be apparent, the imaging system can be used to image anyarbitrary object other than human feet or body part, as long as theobject interrupts the imaged background pattern. Those skilled in theart can make enhancements, improvements, and modifications to theinvention, and these enhancements, improvements, and modifications maynonetheless fall within the spirit and scope of the following claims.

What is claimed is:
 1. A method of imaging an object, the methodcomprising the steps of, disposing the object in front of a surfacehaving patterned areas and a reference area, the object providing anobject image, the object being disposed in front of the patterned areasfor obstructing patterned images of the pattern areas positionedrelative to the reference area providing an unobstructed referenceimage, focusing a camera upon the object, upon the patterned areas, andupon the reference areas from differing perspectives at respectiveperspective positions for capturing respective composite images eachcomprising the object image, the patterned images and the referenceimage, generating a data stream of the composite image comprising X rowsand Y columns of an array of pixels, the data stream providing a seriesof transitions indicating regularity of the patterned images, a durationbetween each of the transitions indicating a number of pixels along oneof the X rows and Y columns of the array of pixels, area determiningalong one of the rows or columns of the array of pixels the number ofpixels between each of the transitions for determining an interruptionin regularity of number of pixels between each of the transitions forindicating where the object obstructs the patterned areas at anobstructed pattern area of one of the patterned areas for indirectlyindicating the 2D edge point of the object, and 2D determining adistance between the reference area and obstructed patterned area fordetermining the 2D edge point of the object relative to the referencearea.
 2. The method of claim 1 wherein the method further comprises thesteps of, repositioning the camera at differing positions, and repeatingthe focusing, area determining and 2D determining steps for each of thediffering positions for providing respective 2D edge points.
 3. Themethod of claim 2 further comprising the step of, 3D determining a 3Dedge of the edge of the object from the 2D edge points.
 4. The method ofclaim 2 further comprising the step of computing dimensions of theobject from the 2D edge points.
 5. The method of claim 2 wherein theobject is a foot, and the patterned areas are checkerboard areas.
 6. Themethod of claim 5 further comprising the set of computing dimensions ofthe foot from the 2D edge points.
 7. The method of claim 6 wherein thedimensions comprising foot length, foot width, arch height and forefootheight.
 8. The method of claim 2 further comprising the step of, 3Ddetermining 3D edge points of the edge of the object from the 2D edgepoints.
 9. The method of claim 8, further comprising the step of,computing dimensions of the object from the 3D edge points.